The control plane for enterprise AI infrastructure. One platform.
We work with
AI & LLM
Cloud & infrastructure
AI Workload Orchestration
Provision and run models, agents, and AI services across AWS, Azure, GCP, Kubernetes, and on-prem.
Governance & Policy Control
Define who can use which models, tools, agents, and infrastructure — with policy enforcement built in.
Cost Visibility & Spend Control
Track AI usage and infrastructure cost by team, workload, model, environment, and project.
Auditability & Security
Capture activity across models, agents, tools, and infrastructure so teams can prove what ran and where.
Why PhantomAgent
AI adoption creates a new infrastructure problem. Models are fragmented across providers. Agents need secure access to tools and data. Spend can grow without clear ownership. Teams need governance without slowing innovation — and enterprises need the option to run workloads internally. PhantomAgent helps companies move from scattered AI experiments to governed enterprise AI operations.
- model fragmentationsecure tool accessspend ownership
Self-hosted model enablement
Support internally hosted models for sensitive workloads, cost control, compliance, and reduced vendor dependency — without losing centralized governance across your AI ecosystem.
Tim Gruber
Chief Revenue Officer
The vision
As AI becomes core infrastructure, enterprises need more than access to models. They need control. PhantomAgent provides the foundation for a centralized AI control plane — helping organizations govern usage, control spend, improve reliability, and avoid vendor lock-in across their AI ecosystem.
- GovernanceSpend controlReliabilityVendor independenceSelf-hosted modelsEnterprise auditability
Provision, orchestrate, govern, and audit
AI workloads across your infrastructure.
Run models, agents, and AI services across cloud, on-prem, and customer-owned infrastructure with one platform.
Push-Button AI Workload Orchestration.
Provision and run models, agents, and AI services across AWS, Azure, GCP, Kubernetes, and on-prem.
Self-Hosted Model Enablement.
Run internally hosted models for sensitive workloads, cost control, compliance, and reduced vendor dependency.
Governance & Policy Control.
Define who can use which models, tools, agents, and infrastructure — with policy enforcement built into the platform.
Cost Visibility & Spend Control.
Track AI usage and infrastructure cost by team, workload, model, environment, and project.
Failover & Reliability.
Route workloads across healthy infrastructure and reduce dependency on a single provider, region, or AI service.
Auditability & Security.
Capture activity across models, agents, tools, and infrastructure so teams can prove what ran, where it ran, and what it accessed.
Built for Enterprise AI Teams
Enterprise AI Teams
Design Partner Program
Explore PhantomAgent as a design partner. Contact us to learn more.